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Effectiveness of Models Used to Deliver Multimodal Care for Chronic Musculoskeletal Pain: a Rapid Evidence Review

  • Kim Peterson
  • Johanna Anderson
  • Donald Bourne
  • Katherine Mackey
  • Mark Helfand
Review Paper

Abstract

Background

Primary care providers (PCPs) face many system- and patient-level challenges in providing multimodal care for patients with complex chronic pain as recommended in some pain management guidelines. Several models have been developed to improve the delivery of multimodal chronic pain care. These models vary in their key components, and work is needed to identify which have the strongest evidence of clinically-important improvements in pain and function. Our objective was to determine which primary care-based multimodal chronic pain care models provide clinically relevant benefits, define key elements of these models, and identify patients who are most likely to benefit.

Methods

To identify studies, we searched MEDLINE® (1996 to October 2016), CINAHL, reference lists, and numerous other sources and consulted with experts. We used predefined criteria for study selection, data abstraction, internal validity assessment, and strength of evidence grading.

Results

We identified nine models, evaluated in mostly randomized controlled trials (RCTs). The RCTs included 3816 individuals primarily from the USA. The most common pain location was the back. Five models primarily coupling a decision-support component—most commonly algorithm-guided treatment and/or stepped care—with proactive ongoing treatment monitoring have the best evidence of providing clinically relevant improvement in pain intensity and pain-related function over 9 to 12 months (NNT range, 4 to 13) and variable improvement in quality of life, depression, anxiety, and sleep. The strength of the evidence was generally low, as each model was only supported by a single RCT with imprecise findings.

Discussion

Multimodal chronic pain care delivery models coupling decision support with proactive treatment monitoring consistently provide clinically relevant improvement in pain and function. Wider implementation of these models should be accompanied by further evaluation of clinical and implementation effectiveness.

KEY WORDS

multimodal multidisciplinary musculoskeletal pain chronic pain rapid review 

Notes

Acknowledgements

The VA Evidence-based Synthesis Program (ESP) is funded by Quality Enhancement Research Initiative (QUERI). The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of QUERI. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the US Government.

Compliance with Ethical Standards

Conflicts of Interest

The authors declare that they do not have a conflict of interest.

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Copyright information

© Society of General Internal Medicine (outside the USA) 2018

Authors and Affiliations

  • Kim Peterson
    • 1
  • Johanna Anderson
    • 1
  • Donald Bourne
    • 1
  • Katherine Mackey
    • 1
  • Mark Helfand
    • 1
  1. 1.Department of Veterans AffairsVA Portland Health Care System, Evidence-based Synthesis Program (ESP) Coordinating CenterPortlandUSA

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